Information Retrieval engines are configured to retrieve documents that are relevant to informational goals of a user responsive to receipt of a query from the user. Oftentimes it is difficult for a particular user to formulate a query that will result in the retrieval of information that is desired by the user. As the amount of information that is available to the users on Desktops, Enterprise Networks, Social Networks and the World Wide Web continues to rapidly grow, the tasks of providing relevant information responsive to receipt of a user query becomes increasingly difficult, even as Information Retrieval technology becomes more sophisticated.
An approach that has been successfully utilized to help users locate relevant information is the provision of suggested queries to the user, wherein the suggested queries are based upon other queries previously issued by other users of the search engine. Generally, the suggested queries provided to the user by the Information Retrieval engine have previously been successful in retrieving information that is relevant to users. For instance, query logs can indicate that when a certain query is issued, issuers of the query select a search result that is presented on a first search results page—which indicates that the query is properly formulated to return a search result that is relevant to informational goals of the users.
An exemplary form of Information Retrieval pertains to retrieving a particular document that is known to a user from a document corpus, which is in contrast to retrieving certain information without having knowledge of a certain document that includes such information. When a certain document is desirably located, query suggestions are generally not provided to users. Example situations where users desire to search for a particular document include the search for a particular email in an email inbox of the user, a search for a particular document stored on a hard drive of a computer of the user, etc. In such situations, query logs are either unavailable or not helpful, as there are an insufficient number of previously issued queries to learn which queries were beneficial to the user when the user performed a search over a document store using such queries.
Accordingly, if a user wishes to perform a search over an email inbox, the user must formulate a query and provide such query to a search algorithm in the email application. Many individuals have thousands, tens of thousands, or even hundreds of thousands of emails that are retained in their inboxes. Therefore, a query that is insufficiently specific may result in the provision of a relatively large number of search results, which may be cumbersome for the user to sift through to locate the desired document. The user can attempt to filter the search results by sender, date, or the like, or may attempt to reformulate the query until the desired document is located. The process of formulating queries, reviewing search results, and re-formulating queries to locate a desired document is a time-consuming and frustrating exercise to most users.